Method for distinguishing follicular thyroid adenoma (FTA) from follicular thyroid carcinoma (FTC)

ABSTRACT

Follicular thyroid adenoma (FTA) is distinguished from follicular thyroid carcinoma (FTC) by comparing amount of an expression product of at least one gene selected from the group consisting of DDIT3, ARG2, ITM1, Clorf24, TARSH, and ACO1 in a test follicular thyroid specimen to a normal control thyroid specimen. The test follicular thyroid specimen is identified as FTA if the amount of expression product of TARSH is equal to or greater in the test follicular thyroid specimen than in the normal control thyroid specimen. The test follicular thyroid specimen is identified as FTC if the amount of expression product of DDIT3, ARG2, ITM1, Clorf24, or ACO1 is greater in the test follicular thyroid specimen than in the normal control thyroid specimen.

The U.S. Government retains certain rights to this invention due tofunding by the National Institutes of Health contract number NIH98X-S146A.

FIELD OF THE INVENTION

The invention relates to the field of distinguishing thyroid diseases,and more particularly to the field of distinguishing follicular thyroidadenoma from follicular thyroid carcinoma.

BACKGROUND OF THE INVENTION

The incidence of thyroid cancer is increasing, with a global estimate ofone-half million new cases this year. Thyroid carcinoma is usually firstsuspected by a physician when a solitary nodule is palpated on physicalexam. Thyroid nodules, however, can be the result of a wide spectrum ofcauses, and a major concern is to accurately differentiate betweenbenign and malignant nodules.

Cytology of a fine-needle aspiration (FNA) biopsy is the most widelyused and cost-effective pre-operative test for initial thyroid nodulediagnosis (1). When FNA findings are diagnostic of papillary thyroidcarcinoma, the specificity for malignancy approaches 95% (2). A commonproblem in clinical practice, however, is evaluation and management ofthyroid tumors with a follicular pattern. FNA cytology cannotdifferentiate between follicular thyroid adenoma (FTA) and follicularthyroid carcinoma (FTC). Since cytology cannot distinguish between FTAand FTC they are often grouped together as indeterminate orfollicular-patterned thyroid lesions. Surgical biopsy is needed toconfirm FTA or FTC. Invasion through the tumor capsule or the bloodvessels is an indicator of FTC. To provide an accurate diagnosis, mostguidelines recommend surgical removal of a nodule diagnosed as having afollicular pattern. Complete thyroid resection and subsequentradioiodine therapy is indicated for those patients who ultimately havefindings indicating carcinoma. Overall, only 8%-17% of thesecytologically suspicious nodules are indeed malignant on histologicalexamination (3).

Several genes have been reported to be associated with thyroid tumors.LGALS3 expression was proposed as a potential marker for pre-operativediagnosis of thyroid carcinoma (4-6). Subsequent findings, however,showed LGALS3 expression in benign lesions such as multinodular goiterand FTA (7,8). Recently, a chromosomal translocation t(2;3)(q13;p25) wasreported in five of eight cases with FTC, but not in twenty cases withFTA (9). The authors suggested that the resulting PAX8/PPARG fusion genecould be useful in the diagnosis and treatment of thyroid cancer (9).This rearrangement, however, was found in 13%-30% of follicular adenomas(10-12). In addition, several molecular markers have been analyzed fortheir ability to discriminate between benign and malignant folliculartumors. The molecular markers include TPO, TP53, telomerase, and HMBE-1.Nonetheless, these candidate markers have not proved to have practicalvalue for FNA pre-operative diagnosis of FTC (13-15). More recently cDNAarray technology has been used to identify potentially important thyroidcancer-associated genes (16). Although many of the gene or gene patternsexpressed in thyroid tumors have been described, the clinical problem ofdistinguishing FTC from FTA remains.

A large percentage of patients would, therefore, benefit greatly fromimproved diagnosis of FNA material. Improved diagnosis could reduce thenumber of surgeries, long-term health costs and post surgicalcomplications. In particular, in many areas of the world where healthcare systems are over-burdened, limited resources for surgery could bedirected more rapidly towards those with the highest risk of havingcarcinoma. Accurate molecular markers based on differential geneexpression between FTA and FTC would be one means of improving theaccuracy of diagnoses made from FNA.

BRIEF SUMMARY OF THE INVENTION

In one embodiment of the invention a method for distinguishingfollicular thyroid adenoma (FTA) from follicular thyroid carcinoma (FTC)is provided. Amount of an expression product of at least one geneselected from the group consisting of DDIT3, ARG2, ITM1, Clorf24, TARSH,and ACO1 in a test follicular thyroid specimen is compared to the amountin a normal control thyroid specimen. The expression product is selectedfrom the group consisting of protein and RNA. The test follicularthyroid specimen is identified as FTA if the amount of expressionproduct of TARSH is equal to or greater in the test follicular thyroidspecimen than in the normal control thyroid specimen or the testfollicular thyroid specimen is identified as FTC if the amount ofexpression product of DDIT3, ARG2, ITM1, Clorf24, or ACO1 is greater inthe test follicular thyroid specimen than in the normal control thyroidspecimen.

In another embodiment of the invention a method for distinguishingfollicular thyroid adenoma (FTA) from follicular thyroid carcinoma (FTC)is provided. Amount of an expression product of DDIT3, ARG2, and ITM1 ina test follicular thyroid specimen is compared to the amount in a normalcontrol thyroid specimen. The expression product is selected from thegroup consisting of protein and RNA. The test follicular thyroidspecimen is identified as FTC if the amount of expression product ofDDIT3, ARG2, or ITM1 is increased in the test follicular thyroidspecimen relative to the normal control thyroid specimen. The inventionthus provides the art with methods for distinguishing follicular thyroidadenoma from follicular thyroid carcinoma.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows relative expression level determined by quantitative RT-PCRin twenty three samples of FTA and FTC (black bars) and in normalthyroid tissues (gray bars). Transcript levels were normalized to theaverage of ribosomal protein 8 and t-complex 1, which were uniformlyexpressed in all three thyroid SAGE libraries. Numbers 1-10 correspondto FTA and 11-23 to FTC as described in Table 2. The statisticalanalysis of RT-PCR values revealed that expression of genes DDIT3, ARG2,and ITMI were significantly different at the 0.05 level, and Clorf24 wassignificant at the 0.10 level. Genes ACO1 and TARSH may be involved inpathogenesis of thyroid tumor as well.

FIG. 2 shows quantitative RT-PCR products of three statisticallysignificant genes (ITM1, ARG2, and DDIT3). The samples shown are FTAs(A), FTCs (C), normal thyroid tissues (N), thyroid carcinoma cell lines(CL) and negative control (NC). Genes DDIT3, ARG2, and ITM1 areexpressed in most of the FTCs, the thyroid follicular carcinoma cellline (CL1), the papillary thyroid carcinoma cell line (CL2), and theundifferentiated thyroid carcinoma cell line (CL3), but not in normaland most FTAs. Case 6 (A6) expressed ARG2 and ITM1 and was misclassifiedaccording to our class-predicted genes. Universal human RNA (HUR) wasused as a control. Ribosomal protein 8 is shown as a calibrator gene.The 100-bp DNA ladder (M) is shown in the far left and far right lanes.The results are shown in triplicate, and the numbers correspond to casesanalyzed (Table 2). The product sizes are summarized in Table 3.

FIGS. 3A to 3L show immunohistochemical analysis of DDIT3 (FIGS. 3A-3F)and ARG2 (FIGS. 3G-3L) in paraffin embedded sections of FTA tissue andFTC tissue. FTC tissue exhibited strong brown immunostaining for DDIT3(FIGS. 3D, 3E and 3F) and ARG2 (FIGS. 3J, 3K and 3L). In contrast, FTAtissue (FIGS. 3A, 3B, 3C, 3G, 3H and 3I) exhibited no immunoreactivity.The arrow in FIGS. 3D and 3F shows the vascular invasion in the FTCtissue and the follicular cells that are positive for DDIT3. The arrowin FIG. 3L shows normal thyroid tissue that was negative for ARG2adjacent to a tumor area that was positive for ARG2. Hematoxylin wasused as a nuclear counter stain. Original magnification is X100 forFIGS. 3A-3E and 3G-3L, X40 for FIG. 3F.

DETAILED DESCRIPTION OF THE INVENTION

It is a discovery of the present inventors that follicular thyroidadenoma (FTA) can be distinguished from follicular thyroid carcinoma(FTC) without removing the thyroid or obtaining a surgical sample of thethyroid. In particular, the inventors have discovered that FTA can bedistinguished from FTC by comparing the amount of expression product ofone or more of DDIT3¹, ARG2², ITM1³, Clorf24⁴, ACO1⁵, and TARSH⁶ in atest follicular thyroid specimen to the amount of expression product ina normal control thyroid specimen.¹ DNA-damage-inducible transcript 3D (SEQ ID NOS: 1 and 2)² arginase type 2D (SEQ ID NOS:3 and 4)³integral membrane protein ID (SEQ ID NOS:5 and 6)⁴ chromosome 1 open reading frame 24 (SEQ ID NOS:7 and 8)⁵ soluble aconitase 1 (SEQ ID NOS:9 and 10)⁶NESH binding protein (SEQ ID NOS: 11 and 12)

TARSH expression is indicative of FTA, while expression of DDIT3, ARG2,ITM1, Clorf24, and ACO1 is indicative of FTC. Thus, if the amount ofTARSH expression product is equal to or greater in the test follicularthyroid specimen than in the normal control thyroid specimen then thetest follicular thyroid specimen can be identified as FTA. If the amountof any one, or more of DDIT3, ARG2, ITM1, Clorf24, and ACO1 expressionproduct is greater in the test follicular thyroid specimen than in thenormal control thyroid specimen then the test follicular thyroidspecimen can be identified as FTC.

The amount of RNA expression in a test follicular thyroid specimen or anormal control thyroid specimen can be determined by methods well knownin the art for measuring RNA expression. Examples of such methodsinclude, but are not limited to, reverse transcriptase-polymerase chainreaction (RT-PCR), microarray analysis, northern blot analysis,differential hybridization, and ribonuclease protection assay. Suchmethods are well known in the art and are described in Sambrook et al.,MOLECULAR CLONING: A LABORATORY MANUAL, Second Edition, Cold SpringHarbor Laboratory, Cold Spring Harbor, N.Y., 1989 and Ausubel et al.,CURRENT PROTOCOLS IN MOLECULAR BIOLOGY, John Wiley & Sons, New York,N.Y., 1989.

The amount of protein expression in a test follicular thyroid specimenor a normal control thyroid specimen can be determined by methods wellknown in the art for measuring protein expression. Such methods include,but are not limited to, immunohistochemical staining, ELISA,immunoprecipitation, western blot (immunoblot), radioimmuno assay (RIA),and fluorescence-activated cell sorting (FACS). Such methods aredescribed in Sambrook (1989) and Ausubel (1989).

Follicular thyroid specimens are obtained from a thyroid of a human anddetermined histologically to have a follicular pattern, if a precisediagnosis is not achievable. The specimen can be obtained by any methodknown in the art for obtaining a thyroid specimen. Fine-needleaspiration (FNA) biopsy sampling is an exemplary method. The testfollicular thyroid specimen can be obtained prior to removal of thethyroid. However, the specimen can also be surgically removed thyroidtissue. A normal control thyroid specimen can be, for example, an FNAbiopsy from a patient with a normal thyroid. Alternatively universalreference total human RNA or normal thyroid total RNA can be used as thenormal human control thyroid specimen. Similarly universal referencetotal human protein or normal human thyroid total protein can be used asa control.

Differential expression between test and control samples are used tomake a diagnostic determination. The amount of difference observed willdepend on the particular gene, or the type of expression product, or theassay method, and on sample preparation. Generally, however, adifference which is reproducible or statistically significant can beused. Differences of at least 2-fold, 5-fold, 10-fold, 20-fold, 25-fold,have been observed and can be used to make a diagnosis. Genes which arenot observably expressed in one of the two forms of follicular thyroidspecimen may be compared without precise quantitation, for examplevisually.

DDIT3, also named GADD153 (growth arrest and DNA-damage inducible 153gene), encodes a transcription factor that is induced in response to alarge spectrum of genotoxic agents such as UV light, hypoxia, nutrientdeprivation, environmental toxicants, and certain DNA-damaging agents(32,33). When induced, DDIT3 inhibits cell proliferation and promotesrepair and/or apoptosis. The induction of DDIT3 leads to distinctbiologic effects, such as growth stimulation, differentiation,invasiveness, and migration (34).

ITM1 encodes a highly conserved protein that contains ten to fourteenmembrane-spanning domains. The protein does not have any identifiabledomains with enzymatic activity and is probably not involved in directtransmembrane signaling. In addition, the transmembrane domain of ITMIdoes not present any features of a transporter protein, such as an ATPbinding cassette. However, Hong et al. hypothesize that ITM1 is a noveltype of permease/transporter membrane protein (42). In humans, the ITM1gene was mapped to human chromosome 11q23.3 (43,44). Interestingly, lossof heterozygosity was found in follicular adenomas at 11q (45,46).

ARG2 encodes an enzyme that catalyzes the hydrolysis of arginine toornithine plus urea. At least two isoforms of mammalian arginase exists(ARG1 and ARG2). The two isoforms differ in their tissue distribution,subcellular localization, immunologic crossreactivity, and physiologicfunction (38). The type II isoform is located in the mitochondria and isexpressed in extra-hepatic tissues, especially in the kidney (39). Thephysiologic role of this isoform is poorly understood, but it may play arole in nitric oxide and polyamine metabolism (40). Since polyamines arevital for cell proliferation, it is possible that the increased level ofornithine, due to the elevated arginase activity, may be linked tocarcinogenesis development (41).

Clorf24 was described as a candidate marker for renal tumor, especiallyin early-stage renal carcinogenesis. The pattern of gene expressionshowed that Clorf24 is expressed in normal muscle, pancreas, colon, andprostate. The gene is very conserved in humans and rats, but the proteinfunction is still unknown. A similarity with the DNAJ-1 motif, part of achaperone system, has been described (47).

TARSH encodes a protein containing an Src-homology 3 (SH3) biding motif,a nuclear target sequence with no catalytic domain. Its biochemical andphysiologic role has not been identified. TARSH is thought to be abinding partner of NESH-SH3, a member of the E3B1/ArgBP/Avi2/NESH family(48). Members of this family are involved in membrane ruffling andlamellipodia formation, which suggests that the loss of their expressioncould be involved in the mechanism of cell motility and metastasis.Re-expression of NESH suppresses motility and metastasis disseminationin the U-87 MG malignant glioma cell line (49). Although the bindingactivity between NESH and TARSH is yet to be confirmed, the loss ofTARSH expression in FTCs might be a mechanism by which the follicularcells acquire motility and promote invasion. Another fact that supportsthis hypothesis is that the TARSH gene was mapped at 3q12, where loss ofheterozygosity was found in FTC but not in FTA (50,51). Loss ofheterozygosity in 3q was also correlated with survival in FTC (52).

Aconitase 1 (ACO1), also known as iron regulatory element bindingprotein 1 (IREB1), is a cytosolic protein which binds to iron-responsiveelements (IREs). IREs are stem-loop structures found in the 5′untranslated region (UTR) of ferritin mRNA, and in the 3′ UTR oftransferrin receptor mRNA. The iron-induced binding of ACO I to the IREresults in a repression of ferritin mRNA translation. Transferrinreceptor mRNA is rapidly degraded, however, iron-induced binding of ACO1 to the IRE results in an inhibition of this rapid degradation. Thus,ACO I plays a central role in cellular iron homeostasis.

All patents patent applications and references cited in this applicationare incorporated herein by reference in their entirety.

The following examples are offered by way of illustration and do notlimit the invention disclosed herein.

EXAMPLES Example 1

Identification of Diagnostic Markers by SAGE Analysis to Distinguish FTAfrom FTC

To directly address the problem of finding diagnostic markers that woulddistinguish FTA from FTC, gene expression was quantified in FTA tissues,FTC tissues, and normal thyroid tissues using serial analysis of geneexpression (SAGE) (17). SAGE counts cDNA transcript tags in largenumbers. Thus, SAGE analysis makes it possible to identify a restrictedset of genes that are highly expressed in one tissue and not detectablein another. Transcript counts from FTC, FTA, and normal thyroidlibraries were generated and compared.

SAGE Libraries.

One follicular thyroid adenoma, one follicular thyroid carcinoma, andone normal thyroid were chosen for SAGE (17). SAGE libraries wereconstructed using a microSAGE procedure (19) and were sequenced throughthe SAGE portion of the Cancer Genome Anatomic Project (20). Tags wereextracted from automated sequence text files; and duplicate ditags,linker sequences, and repetitive tags were removed using SAGE 2000software version 4.12. The Monte-Carlo simulation function (26) of theSAGE 2000 program was used to determine P values of differentiallyexpressed genes. The full set of tag counts for all three libraries areavailable for downloading or analysis at the Cancer Genome AnatomyProject SAGE Genie Web site (21).

SAGE Analysis.

SAGE analysis of gene expression in FTA tissues, FTC tissues, and normalthyroid tissues resulted in a total of 359,478 tags. This represented116,037 unique transcript tags. A SAGE tag sequence error rate of 6.8%(26) was used and we estimated that a total of 108,146 uniquetranscripts were detected. Of those, 10,048 were detected at least fivetimes and 32,748 were detected at least two times.

Two comparisons were performed using SAGE 2000 software version 4.12:one between normal thyroid and FTA and one between FTA and FTC. UsingSAGE software to perform Monte Carlo simulations (26), the expressionlevel of 305 genes were found to be statistically significant if Pvalue≦0.0001. Of those 305 genes, seventy-three genes were found to beexpressed only in FTC or only in FTA and normal thyroid tissue.Thirty-seven of these 305 transcripts were highly expressed in FTCtissues and not expressed in FTA or normal tissues. Thirty-six of the305 genes were highly expressed in FTA and normal tissues and notexpressed in FTC tissues.

Among the seventy-three candidates genes, those with the greatestfold-induction or fold-repression in FTC were first considered.Accordingly, seventeen transcripts were selected for RT-PCR validation.Twelve transcripts were highly expressed in the FTC library and fivewere expressed only in FTA and normal thyroid libraries. The expressionlevels of these genes in FTA and FTC libraries ranged from 43- to10-fold. Table 1 lists the seventeen genes. For comparison, thetranscript levels for well-characterized genes for normal thyroidphysiology are also presented. TABLE 1 Validated FTA and FTCdifferentially expressed genes and thyroid specific genes GenBankAccession (SEQ ID NOS: Tag Nor- Ade- Carci- Transcript nucleotide/ Genesequence mal⁷ noma⁷ noma⁷ description⁸ amino acid) Location ontology⁹Transcripts up regulated in FTC AACAATTGGG (SEQ ID NO:79) 0 0 19 DDIT3 -DNA-damage- NM_004083.2 (SEQ ID NOS:1/2) 12q13.1 Regulation inducibletranscript 3D¹⁰ cell cycle TTTCACAACA (SEQ ID NO:80) 2 0 21 ARG2 -arginase, type II D¹⁰ NM_001172.2 (SEQ ID NOS:3/4) 14q24 Urea cycleTATTTACTCT (SEQ ID NO:81) 1 0 15 Clorf24, Chromosome 1 open NM_052966(SEQ ID NOS:5/6) 1q25 ND reading frame24 TTGTAAATTA (SEQ ID NO:82) 0 019 PCSK2-proprotein convertase NM_002594 (SEQ ID NOS:13/14) 20p11.2Cell-cell subtisiLin/kexin type 2 signaling CTGTAAATAT (SEQ ID NO:83) 00 12 ODZ1 (odd Oz/tenascin-M NM_014253 (SEQ ID NOS:15/16) Xq25Proteolysis Drosophila melanogaster) and homolog 1 PeptidolysisGATAGGTCGG (SEQ ID NO:84) 0 0 27 ACO1, aconitase 1, soluble NM_002197(SEQ ID NOS:7/8) 9p22 Negative regulation of translation AGCTGAGCTA (SEQID NO:85) 3 0 11 DNASE2, deoxyribonuclease II NM_001375 (SEQ IDNOS:17/18) 19p13 DNA lysosomal metabolism TAATGTATTC (SEQ ID NO:86) 1 023 Hypothetical protein FLJ13576 NM_022484 (SEQ ID NOS:19/20) 7q31.32 NDGCTTTACTTT (SEQ ID NO:87) 5 0 27 ITMI-Integral membrane NM_152713 (SEQID NOS:9/10) 11q23 Protein amino protein ID¹⁰ acid glycosylationTAAATACTTG (SEQ ID NO:88) 1 0 43 PDK4-Pyruvate dehydrogenase NM_002612(SEQ ID NOS:21/22) 7q21.3 Signal kinase 4 transduction GCGCATCAAA (SEQID NO:49) 0 0 15 LOC92196, EST weakly similar XM_043500 (SEQ IDNOS:23/24) 2q24 Apoptosis to death-associated protein 1 AGCAGGGCTC (SEQID NO:90) 4 0 17 PPP1R14B - protein phosphatase XM_370630 (SEQ IDNOS:25/26) 11q13 Cell-cell 1, regulatory subunit 14b signalingTranscripts up regulated in FTA CAGATAAGTT (SEQ ID NO:91) 3 12 0COL14A1, collagen, type XIV, XM_044622 (SEQ ID NOS:27/28) 8q23 Cell-cella1 (undulin) adhesion CTTCAATCTT (SEQ ID NO:92) 7 37 0 TARSH- target ofNESH-SH3 NM_015429 (SEQ ID NOS:11/12) 3q12 ND protein GAGAGGAAGG (SEQ IDNO:93) 3 34 0 Putative Emu1 NM_133455.1 (SEQ ID NOS:29/30) 22q12.2 NDTGATCAATAT (SEQ ID NO:94) 3 10 0 NID2 NM_007361.1 (SEQ ID NOS:31/32)14q21 Cell adhesion GGTATGCTGT (SEQ ID NO:95) 2 10 0 EDNRB, Endothelialreceptor NM_000115.1 (SEQ ID NOS:33/34) 13q22 G-protein type B coupledreceptor pathway Genes involved in thyroid function GATGAATAAA (SEQ IDNO:96) 75 38 0 TPO, Thyroid peroxidase M17755 (SEQ ID NOS:35/36) 2p25Thyroid hormone generation CGGTGAAGCA (SEQ ID NO:97) 134 67 130 TG,Thyroglobulin NM_003235 (SEQ ID NOS:37/38) 8q24.2 Thyroid hormonegeneration ATGCTAAGAG (SEQ ID NO:98) 30 13 63 DIO2, Deiodinase,NM_000793 (SEQ ID NOS:39/40) 14q24.2 Thyroid iodothyronine, type IIhormone generation⁷SAGE tags counts shown are after normalization to 100,000.⁸Tag sequences were mapped to transcript sequence, confirmed by PCR andused to determine gene name and accession number.⁹Gene classification was by biological process, ND- gene classificationnot defined.¹⁰Genes differentially expressed in this study.

Four genes, DDIT3, ARG2, ITM1, and Clorf24, were found to havesignificant differential expression on an independent set of tumors.Interestingly, DDIT3, ARG2, and ACO1 can be modulated by hypoxia(33,55). Thus, we looked for CA9 expression in thyroid cancer since itis a hypoxia marker in other tumors (56). A higher expression of CA9 wasfound in 2 cases of FTCs which had a higher level of DDIT3 and ARGexpression, but was not found in FTAs and normal tissues. Furthertesting is needed to determine whether hypoxia detected by CA9 is amarker for survival in thyroid carcinomas as it is in other tumors (57).

In addition to the markers of the present invention, SAGE also allowedidentification of new genes, which mapped to a chromosome region thathas already been described as important in thyroid carcinogenesis. A newhypothetical protein, FLJ13576, mapped to 7q31-32, and wasover-expressed in 70% of FTC and the 2 FTA cases (cases 6 and 8, Table2). This hypothetical protein contains a fibronectin type III domain,one of three types of internal repeats within the plasma proteinfibronectin. The 7q31-32 locus contains other genes involved in thyroidcarcinogenesis, such as the MET oncogene (53,54). Other genes mapped inthis region were found such as SLC26A4 (solute carrier family 26, member4) and NRCAM (neuronal cell adhesion molecule) and were foundoverexpressed in the FTC SAGE library. These results, in agreement withthose obtained from comparative genomic hybridization analysis, wherethe observed gain of 7q31 and 7q21.1- q21.2 was the most frequentchromosomal imbalance in FTC, suggest that this locus duplication couldbe involved in thyroid carcinogenesis (51).

Since follicular cell interaction and differentiation is guided by avariety of factors, such as extracellular matrix glycoprotein andreceptor and cell adhesion molecules, we also expected to find genesinvolved in this process to be differentially expressed between FTC andFTA. In fact, ODZ1 (tenascin M), ANX41 (annexin 1), LAMBI (laminin beta1), MYL6 (myosin, light polypeptide 6), MSN (moesin), CLU (clusterin),TMSB4X (thymosin, beta 4), SPARC (osteonectin), CLDN1 (claudin 1), NID2(nidogen 2), Emu 1, CANX (calnexin), SDC2 (syndecan 2), FMOD(fibromodulin), CDH1 (cadherin 1) and COL14A1 (undulin) were founddifferentially expressed in thyroid SAGE libraries. Some of these geneswere described previously as being involved in thyroid tumor genesis,but they were not used to discriminate between FFA and FTC (30,58).

Example 2

RT-PCR Analysis of Genes Identified by SAGE Analysis to ConfirmExpression Level

To validate the differential gene expression profile predicted by SAGE,seventeen genes with the highest fold-induction were tested and analyzedfor gene expression by quantitative real-time RT-PCR.

Tissue Samples.

For RT-PCR analysis, twenty-three primary tumors were obtained frompatients initially diagnosed with follicular thyroid tumor. The tumorswere frozen immediately after surgical biopsy. All samples were obtainedfrom patients followed at Hospital São Paulo, Universidade Federal deSão Paulo, and Hospital Helópolis, São Paulo, Brazil. The study wasapproved by the Ethics and Research Committees of the UniversidadeFederal de São Paulo and Hospital Heliópolis and was in agreement withthe 1975 Helsinki statement, revised in 1983. A signed letter ofinformed consent was obtained from each patient. All patients receivedpost-surgical radioiodine ablation and suppressive thyroxine therapy.Tumor recurrence was observed in three cases of FTC (Table 2). Tissuehistology confirmed the initial diagnoses, as summarized in Table 2.Samples included ten FTA and thirteen FTC biopsies. In addition, eightpatient-matched normal tissues obtained from patients with FTC (n=5) andFTA (n=3) were analyzed. Universal human reference total RNA(Stratagene, La Jolla, Calif., USA) was used as a control. TABLE 2Clinical and histologic data of patients tested by real time RT-PCR Ageat Nodule Case diagnosis size Recur- PAX8-PPARG No. Diagnosis Sex(years) (mm) rence Rearrangement 1 FTA F 70 34 No Yes 2 FTA F 31 35 NoYes 3 FTA F 29 40 No Yes 4 FTA F 39 40 No NF¹¹ 5 FTA F 44 80 No NF 6 FTAF 51 40 No NF 7 FTA M 45 30 No NF 8 FTA F 52 30 No NF 9 FTA F 12 7 No NF10 FTA F 22 15 No NF 11 FTC F 38 35 No Yes 12 FTC M 28 48 No Yes 13 FTCF 25 32 No Yes 14 FTC F 76 62 Yes Yes 15 FTC F 40 19 Yes NF 16 FTC F 3832 No NF 17 FTC F 48 16 No NF 18 FTC F 36 20 No NF 19 FTC F 45 45 No NF20 FTC F 24 23 No NF 21 FTC M 68 100 Yes NF 22 FTC F 33 30 No NF 23 FTCM 66 90 No NF¹¹Not found in patient.

Cell Lines.

The human follicular thyroid carcinoma cell line UCLA RO-82W-1 (WRO),the papillary thyroid carcinoma line UCLA NPA-87-1 (NPA), and anundifferentiated thyroid carcinoma cell line UCLA RO-81A-1 (ARO) weregrown in DMEM (Invitrogen, Carlsbad, Calif., USA) supplemented with 10%FCS (Invitrogen) in a 5% CO₂ environment at 37° C., as previouslyreported (18).

RNA Isolation, cDNA Synthesis, and Quantitative RT-PCR.

Total RNA was isolated using RNAgents (Promega, Madison, Wis., USA),according to the manufacture's recommendation. One microgram of totalRNA was treated with DNA-free (AMBION, Austin, Tex., USA) and wasreverse-transcribed to cDNA using the Omniscript Reverse Transcriptasekit (QIAGEN, Germantown, Md., USA) with oligo(dT)₁₂₋₁₈ primer and tenunits of RNase inhibitor (Invitrogen). Reverse transcriptase-negativesamples were prepared for each individual reaction and were used ascontrols for detection of assay contamination. The cDNA was then diluted5-fold, and 1.5 μl aliquots were used in 20-μl PCR reactions containing10-μM of each specific primer, 1× IQ Supermix (BioRad, Hercules, Calif.,USA), and SYBR Green (Sigma, St. Louis, Mo., USA). The PCR reaction wasperformed for 40 cycles of a 4-step program: 94° C. for 30 seconds,annealing temperature for 15 seconds, 72° C. for 15 seconds, and afluorescence-read step for 10 seconds. After PCR, a melting curveanalysis was performed and the read temperature of each assay was setabove the melting point of short primer-dimers and below that of thetarget PCR product. Quantitative PCR reactions were performed twice intriplicate. The threshold cycles (Ct) were obtained using iCyclersoftware version 3.0 (BioRad) and were averaged (SD≦1). Gene expressionwas normalized using the average of two control genes (ribosomal proteinS8 and t-complex 1), shown by SAGE to be at equivalent levels in allthree SAGE libraries. A relative expression amount was calculatedaccording to the formula 2^((Rt-Et))/2^((Rn-En)). Rt is the Ct cyclenumber observed in the experimental sample for the two control genes. Etis the Ct cycle number observed in the experimental sample for thereference gene. Rn is the average Ct cycle number observed in tenadenomas for the two control genes. En is the average Ct cycle numberobserved in ten adenomas for the reference gene (22). FIG. 1 shows therelative expression levels of DDIT3, ARG2, ITM1, Clorf24, ACO1, andTARSH in normal tissue samples, ten FTA biopsy samples and thirteen FTCbiopsy samples. The results obtained from fourteen of the seventeenrelative expression levels in twenty-three samples and normal tissueswere used for statistical analysis. Fourteen genes were used becausethree genes showed no difference by PCR. The PCR-specific primers,annealing temperatures, and fluorescence-read temperatures aresummarized in Table 3. The PCR products were resolved by electrophoresisin a 3% agarose/ethidium gel. TABLE 3 Primers and PCR conditions ofselected genes and controls up regulated and down regulated in FTCAnnealing Read Size Gene Primer¹² temp. temp.¹³ (bp)¹⁴ Controls RS8 F:5′ AACAAGAAATACCGTGCCC 3′ (SEQ ID NO:41) 55 83 125 R: 5′GTAGGAACCAGCTCGTTATTAG 3′ (SEQ ID NO:42) TCP1 F: 5′ CACTAGCAGTTAATGCTGCC3′ (SEQ ID NO:43) 57 81 123 R: 5′ TGCTCAAATCAAGACCAATCC 3′ (SEQ IDNO:44) Up regulated DDIT3 F: 5′ GCGACAGAGCCAAAATCAGAG 3′ (SEQ ID NO:45)55 84 316 R: 5′ AGTGAGCCAAGCCAGAGAAG 3′ (SEQ ID NO:46) ARG2 F: 5′GAAGGCATGTATATTGCTGAGG 3′ (SEQ ID NO:47) 54 84 204 R: 5′TGAACTGGGAGTAGGAAGTTG 3′ (SEQ ID NO:48) Clorf24 F: 5′GCTTGATGAAACTCTGAAAGTG 3′ (SEQ ID NO:49) 57 86 180 R: 5′AGAACTCCTGGCAGAATGG 3′ (SEQ ID NO:50) PCSK2 F: 5′ CATCCCAGCCCCAATTTTTC3′ (SEQ ID NO:51) 54 86 183 R: 5′ AATACTCCTGTCGCCTCTC 3′ (SEQ ID NO:52)ODZ1 F: 5′ CGGCTTCAGACAAAAACTCAAG 3′ (SEQ ID NO:53) 57 83 180 R: 5′AGAAGGGACAGCAGCAAAC 3′ (SEQ ID NO:54) ACO1 F: 5′ TTTGAGAAAGAGCCATTGGGAG3′ (SEQ ID NO:55) 54 83 300 R: 5′ TAGCAGCACATAGGCATCCAC 3′ (SEQ IDNO:56) DNA SE2 F: 5′ TTCCCTTCGCTGAGTTCTC 3′ (SEQ ID NO:57) 54 87 301 R:5′ ATGCCTACAGTTTTGTGCC 3′ (SEQ ID NO:58) FLJ13576 F: 5′ATTTCAGAGCAGTTGGTGTT 3′ (SEQ ID NO:59) 51.8 82.5 153 R: 5′GTTACCCAATTCATGGAAGA 3′ (SEQ ID NO:60) ITM1 F: 5′ AGGCCTGACTGGGTATTCT 3′(SEQ ID NO:61) 56 85 324 R: 5′ TATCCTGACCAGCCAATGTTC 3′ (SEQ ID NO:62)PDK4 F: 5′ CGCCTGTGATGGATAATTCC 3′ (SEQ ID NO:63) 54 81 120 R: 5′AGCATCTGTTCCATATCCTGA 3′ (SEQ ID NO:64) DAP1 F: 5′ GAAAACAAGTGCCATTGcAAA3′ (SEQ ID NO:65) 53 83 243 R: 5′ GCTAAGCTGTCAGATATTT 3′ (SEQ ID NO:66)PPP1R14B¹⁵ F: 5′ CAGCAGGCGAGAAATGAAG 3′ (SEQ ID NO:67) 54 87 226 R: 5′CGTCAAGTATGACGGCAAG 3′ (SEQ ID NO:68) Down regulated COL14A1 F: 5′CTGCCATCCTCAACCAGATT 3′ (SEQ ID NO:69) 55 88 211 R: 5′AACGCCTGGATTTCCTTTTT 3′ (SEQ ID NO:70) TARSH F: 5′ TACTAGGCCCAAACCCAGTG3′ (SEQ ID NO:71) 54 81 213 R: 5′ CCTGGCTTTCCAGTGACATT 3′ (SEQ ID NO:72)Emu1 F: 5′ TAAGGGAGACCCTGGTGAGAAG 3′ (SEQ ID NO:73) 54 83 131 R: 5′ACCCCAGCTCTGGTTCATAG 3′ (SEQ ID NO:74) NID2 F: 5′ GTGCCGGAGTGGTTATGAGT3′ (SEQ ID NO:75) 54 86 233 R: 5′ TAGCTGCAGGGTGACATCTG 3′ (SEQ ID NO:76)EDNRB16 F: 5′ TCCCGTTCAGAAGACAGCTT 3′ (SEQ ID NO:77) 57 83 231 R: 5′CACGAGGGCAAAGACAAGGAC 3′ (SEQ ID NO:78)¹²Specific primers that corresponded to exon-intron boundaries and weredesigned using Seq Web version 2.¹³Fluorescence-read temperature.¹⁴PCR product size.¹⁵Not confirmed by RT-PCR.¹⁶Not confirmed by RT-PCR.

The results obtained from SAGE were compared with those obtained fromRT-PCR analysis for the samples used to generate FTA and FTC libraries(cases 5 and 12, respectively). When RT-PCR and the original sampleswere used, fourteen of seventeen genes showed the predicted differencebetween FFA and FTC, and three did not.

Using the full panel of samples, nine of twelve FTC samplesover-expressed transcripts maintained high expression in 50%-100% ofFTCs tested, compared with the expression of same transcript in FTA andpatient-matched normal tissue. DDIT3 (DNA-damage-inducible transcript 3)and ARG2 (arginase type II) were expressed at higher levels in FTCs. Theincreased average of expression was≧5-fold in nearly all FTCs and someexhibited at least 11-fold higher levels as predicted by SAGE. The geneITM1 (integral membrane protein 1) was expressed in all FTCs, with lowlevels of expression in six FTAs. The genes Clorf24 (niban) and ACO1(aconitase 1) were expressed in 76% of FTCs, with low but detectableexpression in 40% of FTAs. The hypothetical protein FLJ13576 wasexpressed in 67% of FTCs and in two cases of FTAs (cases 6 and 8). Sixgenes did not distinguish well: ODZ1, PCSK2 (proprotein convertasesubtilisin/kexin type 2), DNASE2 (deoxyribonuclease II, lysosomal),LOC92196 (EST weakly similar to death-associated protein-1), PDK4(pyruvate dehydrogenase kinase4), and PPPIR14B (protein phosphatase-1,regulatory subunit-14B) were expressed in 30%-69% FTCs and in about30%-40% of FTAs.

Of the fine genes predicted to be FTA specific, the TARSH gene was theonly gene expressed at high levels in normal thyroid tissue and FTAtissue and not expressed in FTC tissue. Therefore, TARSH is a marker fordiagnosing FTA. The genes putative Emu1, NID2, COL14A1, and endothelialreceptor type B were expressed in about 60%-80% of FTCs and were notdiscriminatory between FTA and FTC. The RT-PCR results from the sixgenes that appeared to discriminate between FTC and FTA are summarizedin FIG. 1. Although DDIT3 and ITM1 transcripts were elevated in most FTCcases, use of DDIT3 independently, for example, to identify tumors,could misclassify the case 14, which have low levels of DDIT3 butexpress ITM1 and ARG2 at higher levels (FIG. 1).

In addition, the expression levels of selected genes were analyzed inthree well-characterized thyroid cell lines from different types ofthyroid tumors (18, 27, 28). All the transcripts elevated in FTCs (seeTable 1) were expressed in all thyroid cell lines. The expression of thecandidate markers in the pure populations of cultured carcinoma cellsindicates that the expression is due to the malignant component of thetumor. Conversely, the genes down regulated in the FTC library werepresent at lower levels or absent in the cell lines.

PPARG-PAX8 Rearragement

All patient tissue samples tested by RT-PCR were concomitantly testedfor the presence of PPARG-PAX8. Analysis revealed that the rearrangementbetween PPARG-PAX8, previously identified as a FTC marker (9), was foundin about 33% of FTAs, and in 33% of FTC (Nakabashi et al., manuscript inpreparation) and did not distinguish between adenoma and carcinoma(Table 2). The clinical and pathologic information was compared with theresults obtained from quantitative RT-PCR analysis. Using the crossvalidation procedure, the prediction accuracy was estimated to be 83%.Four of the cases were misclassified (cases 6, 8, 13 and 21—Table 2).Case 6, which exhibited DDIT3, ARG2, and ITM1 expression, wasre-evaluated by an experienced pathologist and showed no evidence ofeither capsule or blood vessel invasion. However, Hashimoto'sthyroiditis and positive staining for both ERBB2 and P53 was reported.In case 8, Hashimoto's thyroiditis was also related. A longer follow-upfor both cases will reveal whether they are true FTAs. Case 13 is a FTCthat was diagnosed as minimally invasive. Case 21, however, is a FTCwhere both blood and capsule invasion were present.

Example 3

Analysis of Gene Expression by Immunohistochemical Staining

The expression levels of two genes (DDIT3 and ARG2) were confirmed byimmunohistochemistry. For the immunohistochemical study pathologicmaterials were retrieved from specimens diagnosed with FTC (n=27) andFTA (n=32) at Hospital São Paulo, Federal University of São Paulo in aneight-year period from 1996-2003. Hematoxylin and eosin-stained sectionswere reviewed by an experienced pathologist.

Immunohistochemical Analysis.

Immunohistochemical staining was performed on paraffin-embedded tissuesections (3 μm) placed on 0.1% poly-lysine-coated slides (Sigma),deparaffinized with xylene and rehydrated through a series of gradedalcohols. The endogenous alkaline phosphatase activity was blocked by 3%hydrogen peroxide. After pressure-cooking retrieval (10 mmol/L citratebuffer, pH 7.4 for 2 minutes), the sections were blocked in 1× PBS/0.1%BSA for 1 hour at room temperature and incubated with the first antibodyfor at least 16 hours at 4° C. The labelled streptavidin biotin reagentscomplex was used (DAKO LSAB+ kit, HRP; Dako Corp, Carpinteria, Calif.,USA) with DAB as a substrate (Sigma). Hematoxylin was used as thenuclear counterstain. The slides were mounted in DAKO Faramount mountingmedium (Dako Corp) and were examined by light microscopy. Theimmunopositivity was evaluated by two independent observers in asemiquantitative fashion in which the relative abundance of each antigenwas evaluated by counting 1000 cells in at least five randomly chosenfields of the tissue sections at ×400 magnification and scored asfollows: negative (−), weak (+), moderately abundant (++), and strong(+++). For two of the genes, DDIT3 and ARG2, antibodies werecommercially available. Polyclonal antiserum GADD153, originated againsta peptide mapping at the C-terminus of DDIT3 of human origin, was usedat 1:200 dilution (R-20; Santa Cruz Biotechnologies Inc., Santa Cruz,Calif., USA). Polyclonal antiserum arginase II, raised against arecombinant protein to amino acids 291-354 mapping at the C-terminus ofarginase II of human origin, was used at 1:100 dilution (H-64; SantaCruz Biotechnologies Inc). Monoclonal mouse anti-human von Willebrandfactor VIII was used at 1:25 dilution (M0616; Dako Corp). CA9 mousemonoclonal G250 antibody (gift of E. Oosterwijk, University MedicalCenter, Nijmegen, The Netherlands) was used at 1:400 dilution. Thecontrol for antibody specificity included incubation with rat IgG, usedin the same concentration as the first antibody (Vector Laboratories).Positive and negative controls were included in each run.

The results are summarized in table 4 (to details see Table 5). Stainingfor DDIT3 expression (GADD153 antibody) showed a moderate to strong(++/+++) expression in twenty-three FTCs (85.2%). The staining wasdetected in both the nucleus and the cytoplasm of neoplastic follicularcells (FIGS. 3D, 3E and 3F). Adjacent nonneoplastic thyroid tissue didnot stain. Three of four FTCs negative for DDIT3 staining were FTCminimally invasive (focal capsular and vascular invasion) and one wasmoderately differentiated. No nuclear and cytoplasmic staining inepithelial cells was observed in twenty nine (90.6%) sections from FTAs(FIGS. 3A, 3B and 3C) and IgG-negative controls. A weak or moderatestaining for DDIT3 was found in 3 (9.4%) of FTAs. Two of three werediagnosed as hürthle cell adenoma (HCA) and one was an atypical adenoma(data not shown). Immunohistochemistry analysis revealed the expressionof DDIT3 in three FTAs, which were diagnosed as atypical adenoma andhürthle cell adenoma (Table 5). This results support the idea that somefollicular hürthle tumors should be considered a separate thyroid cancerclass and few FTAs are early in situ carcinomas with malignantpotential. Longer follow-up will be needed to determine whether thesetumors are a less benign variant. In addition, both follicular lesionscoexisted with Hashimoto's thyroiditis, which is a possible source ofdiagnostic error (9). Immunohisotchemistry analysis in a large set ofhürthle adenomas would be necessary to better understand whether the useof additional class predicted gene in combination with DDIT3 and ARG2can better classify these type of follicular lesions or if additionalprofiling is necessary to find new markers for the hürthle subtype.TABLE 4 Immunoreactivity for DDIT3 and ARG2 in FTA and FTC. FollicularThyroid Follicular Thyroid Adenoma Carcinoma Immunoexpression¹⁷ (n = 32)(n = 27) DDIT3 − 29 (90.6%) 4 (14.8%) + 2 (6.3%) 0 ++ 1 (3.1%) 5 (18.5%)+++ 0 18 (66.7%)  ARG2 − 29 (90.6%) 4 (14.8%) + 1 (3.1%) 0 ++ 2 (6.3%) 2(7.4%)  +++ 0 21 (77.8%)  DDIT3/ARG2 (−/−) 29 3 DDIT3/ARG2 (−/+) 0 1DDIT3/ARG2 (+/−) 0 1 DDIT3/ARG2 (+/+) 3 23¹⁷Negative (−), Positive (+). The intensity was scored into threecategories: weak (+), moderate (++), strong (+++)

TABLE 5 Clinical and Pathological features of FTA and FTC analyzed byimmunohistochemistry to DDIT3 and ARG2. Case No. FNA¹⁸ SEX¹⁹ AGE DDIT3²⁰ARG2²⁰ FTA (n = 32)  1 SUS F 23 (−) (−)  2 BNG F 54 (−) (−)  3 SUS F 30(−) (−)  4 SUS F 42 (−) (−)  5 SUS F 39 (−) (−)  6 SUS F 39 (−) (−)  7SUS F 27 (−) (−)  8 SUS F 39 (−) (−)    9²¹ SUS F 16 (++) (+) 10 BNG F47 (−) (−) 11 SUS F 51 (−) (−) 12 SUS F 17 (−) (−) 13 SUS M 42 (−) (−)14 NA F 54 (−) (−) 15 SUS M 74 (−) (−) 16 NA F 22 (−) (−) 17 NA M 51 (−)(−) 18 SUS M 53 (−) (−) 19 SUS F 38 (−) (−) 20 NA M 55 (−) (−) 21 SUS F37 (−) (−) 22 SUS F 38 (−) (−) 23 SUS F 49 (−) (−) 24 SUS F 62 (−) (−)25 NA F 34 (−) (−) 26 BNG F 43 (−) (−) 27 NA F 29 (−) (−) 28 NA F 72 (−)(−) 29 NA F NA (−) (−) 30 NA M 38 (−) (−)  31²² SUS F 34 (+) (++)  32²²SUS F 29 (+) (++) FTC (n = 27) 33 SUS F 68 (+++) (+++) 34 SUS F 17 (++)(+++) 35 SUS F 49 (+++) (+++) 36 SUS F 61 (+++) (+++)  37²³ SUS F 33 (−)(−) 38 SUS F 61 (+++) (+++) 39 NA F 21 (++) (++)  40²⁴ M 75 (−) (++) 41²³ F 23 (−) (−) 42 M 62 (+++) (+++)  43²³ CA M 66 (−) (−) 44 CA M 75(+++) (+++) 45 NA F 60 (+++) (+++) 46 NA F 52 (++) (++) 47 NA F 76 (++)(++) 48 F 47 (+++) (+++) 49 NA F 75 (+++) (+++) 50 M 36 (+++) (+++) 51NA F NA (+++) (+++)  52²³ F 24 (++) (−) 53 NA F 59 (+++) (+++) 54 F 69(+++) (++) 55 NA F 38 (++) (+++) 56 NA M 31 (+++) (+++) 57 F 66 (++)(+++) 58 F 59 (+++) (++) 59 F 34 (+++) (+++)¹⁸Results obtained from FNA biopsy. (SUS) suspicious, non-available(NA), cancer (CA) and benign (BNG).¹⁹Female (F) and Male (M).²⁰Negative (−), Positive (+). The intensity was scored into threecategories: weak (+), moderate (++), strong (+++)²¹Atypical adenoma.²²Hürthle cell adenoma.²³Minimally invasive.²⁴Moderately differentiated

In this study, over expression of DDIT3 transcript was found in FTCs andthyroid cancer cell lines. Immunohistochemistry showed DDIT3 proteinexpression was moderate to strong in twenty three (82.5%) of FTCs, andspecific for the follicular cells of the tumor (FIGS. 3A-3F). Noexpression of DDIT3 was found in four FTCs, three of which werediagnosed as minimally invasive. This observation suggested acorrelation with DDIT3 expression and capsular and vascular invasion.Barden et al. (16), by oligonucleotide array, found the gene DDIT3 upregulated in FTC and the genes putative Emu1 and NID2 up regulated inFTA. The investigators did not validate the expression of these genes ina set of samples. Interestingly, Nikiforova et al. (35) reported that85% of FTC could develop through non-overlapping RAS or PAX8-PPARGpathways. The authors suggested that RAS activation by itself appearsinsufficient to determine malignant growth but may predispose toacquisition of additional genetic or epigenetic alteration that lead toa fully transformed phonotype. Brenner et al. showed a signaling cascadefrom FAS receptor via the G proteins RAS and RAC to JNK/p38-K and thetranscription factor DDIT3 (36). Expression of DDIT3 was also elevatedafter induction with thiazolidinedione via PPARG1 (37). It is thereforepossible that either or both of these pathways activate DDIT3expression.

ARG2 staining was consistently negative in twenty nine of FTAs (90.6%,)and adjacent nonneoplastic thyroid tissue, whereas specific staining wasfound in the cytoplasm of neoplastic follicular thyroid cells in twentythree of FTCs (85.2%) analyzed (FIGS. 3G, 3H, 3I, 3J, 3K and 3L). Allfour FTCs, negative for ARG2 were diagnosed as minimally invasive.

Overall, a moderate/strong expression of ARG2 and DDIT3 were observed in85.2% of FTCs, whereas 90.6% of FTAs were negative, indicating theutility of these antibody to discriminate FTC from FTA. In addition, theimmunoreactivity with both antibodies in FTCs were more often diffusethan focal and stronger intensity in comparison with those observed inthe four cases of FTAs.

Staining with von Willebrand factor VIII was used to distinguishendothelial cells in all tissues. Moderate expression of CA9 wasobserved in 2 FrCs (cases 11 and 12), but not in FTAs and normal tissues(data not shown).

Example 4

Statistical Analysis for a Class Predictor to Differentiate FTA from FTC

To identify genes for which expression levels were statisticallysignificant between FTA and FTC, the relative expression data obtainedfrom RT-PCR analysis on fourteen of seventeen genes (FIG. 1) were used.The initial comparison of expression levels was carried out using rankbased (Wilcoxon rank sum) and mean based (Student's t) tests. Data werelog transformed before applying the, Student's t test. A comparison wasdesignated as statistically significant if either the rank-sum statisticor the corresponding t-statistic was found to be significant, using analpha level that had been adjusted (using a Bonferroni adjustment) tokeep the family wise error rate at 0.10. Next, development of anexpression-based model that could be used to predict class of diagnosisfor the tumor (FTA or FTC) was investigated. The framework outlined byRadmacher et al. (23) was followed, and the prediction method we usedwas the compound covariate predictor for gene expression data (23, 24).The performance of the predictor was tested using leave-one-outcross-validation for all steps of the prediction procedure (i.e.,selection of differentially expressed genes as well as creation of theprediction rule) (23, 25). The significance of the performance of thepredictor using the permutation based test outlined in Radmacher et al.(23) was assessed, in which the class labels are randomly permuted andthe proportion of data sets that have a cross validated error rate assmall as observed in the data set was calculated. Because it wasprohibitive to compute all possible permutations, 2000 randompermutations were used to estimate the achieved significance level. Theconcordance of the results of the immunohistochemistry staining and thepathological identification of class (FTC vs. FTA) was estimated using akappa statistic and constructing a 95% confidence interval (Kramer andFeinstein 1981). The use of kappa corrects for agreements between thetwo methods (immunohistochemistry and pathology) expected by chance. Themaximum value of kappa, corresponding to perfect agreement, is 1.0.Kramer and Feinstein (1981) suggested guidelines to assess thesignificance of the magnitude of the statistic.

Genes were declared different between the 2 groups if the P value wasless than the family-wise error rate of 0.10. The Wilcoxon test showedthat the difference in gene expression of DDIT3, ARG2, and ITM1 wasstatistically significantly at the 0.05 level. Expression of anadditional gene (Clorf24) was statistically significant at the 0.10level. The Student's t test showed that genes DDIT3 and ITM1 weresignificant at the 0.05 level. No additional genes were significant atthe 0.10 level. Thus, expression levels of four genes (DDIT3, ARG2,ITM1, and Clorf24) were declared significantly different between the twogroups; expression levels of DDIT3 and ITM1 were declared significantlydifferent by both analyses.

The class predictor used genes in which expression levels were foundsignificantly different at the 0.10 level using the t test. The sample tstatistics were used as weights in the compound covariate predictor. Toevaluate the predictor, the leave-one-out cross-validation was used: foreach sample, in turn, one sample was left out, and the predictor wasdeveloped on the remaining twenty two samples. The left-out sample waspredicted. All the steps of the prediction procedure were used includingselection of differentially expressed genes, as well as creation of theprediction rule (23, 25). Using leave-one-out cross validation, nineteenof the twenty three (83%) samples were correctly predicted. To assessthe significance of these prediction results, a permutation test (23,25) was implemented. The proportion of random permutations with four orfewer misclassifications was 0.007. Thus, the results of the predictionanalysis were found significant. Two of the genes, DDIT3 and ITM1, werealways selected in each step of the cross validation procedure (i.e.,each time a sample was left out). In the Wilcoxon test, ARG2 wasstatistically significantly at the 0.05 level. An additional gene,Clorf24, expressed in most of the FTCs, can be a predictor. Even whenstarting with only one SAGE library per tumor to predict candidatemarkers, and faced with heterogeneous gene expression in FTA and FTC, wewere still able to find consistent and statistically significantmarkers. However, future studies using this simple SAGE-based method toidentify tumor markers would likely benefit from using two or morelibraries of each representative tumor type. SAGE has been previouslyused for a shallower transcript sampling of thyroid tissue, but notspecifically directed toward distinguishing between FTA and FTC (29-31).Using deep sampling of representative FTC and FTA cases allowedapplication of selection criteria for candidate genes that were likelyto have large differences in expression that could be easily detected byimmunhistochemistry.

FIG. 2 shows the final products for three genes, the differentialexpression of which was shown to be statistically significant at the0.05 level, after running fourty cycles of PCR using templates from FTC,FTA, normal thyroid, and cell lines.

The concordance between the results of the immunohistochemistry stainingon an independent set of tumors and the diagnosis by histopathology wasestimated by kappa. The estimated kappa was 0.76 with a 95% confidenceinterval of [0.59, 0.93]. The value of 0.76 corresponds to a substantialstrength of agreement based on previously developed guidelines (Kramerand Feinstein 1981).

Example 5

TARSH and Its Binding Partner NESH Can Repress Cell Invasion PhenotypeIn Vitro

To investigate whether TARSH and its partner NESH could repress cellinvasion in vitro, TARSH and NESH full-length cDNAs were re-expressed intwo thyroid carcinoma cell lines ARO and WRO. These cell lines have aninvasive phenotype (27, 28).

In Vitro Invasion Assay.

A neomycin-selectable expression vector pcDNA3.1 (Invitogen) containinga full-length wildtype (wt) human TARSH was stably transfected into AROand WRO thyroid carcinoma cell lines. Additionally, a full-length cDNAof NESH, TARSH partner, was transfected into ARO and WRO cell lines(gift of S. Matsuda, Nagoya University School of Medicine, Nagoya,Japan). Cells (5×10⁶) were transfected using Bio-Rad Gene Pulseraccording to the manufacturer's instruction (Bio- Rad). Neomycinresistant colonies were initially selected on plates containing 800μg/mL geneticin (G418; Gibco-BRL, Gaithersburg, Md., USA) and maintainedin culture medium containing 600 μg/mL geneticin. As a control, cellswere transfected with pcDNA3.1 and selected as described above. Twostable transfected clones for TARSH, NESH and a control were selectedand used for an invasion assay using a BD Biocoat Matrigel InvasionChamber as described by the manufacture (Becton Dickson Labware,Bedford, Mass., USA). Briefly, the invasion chamber (with Matrixgelmatrix) and control chamber (without Matrixgel matrix) were rehydratedand 2.5×10⁴ cells were plated to the chambers containing Matrigel matrixand control chamber wells without matrix. Twenty-four hours later, thecells on the lower side of the chambers were fixed and stained withBaxter Diff-Quik stain kit (Dade Behring, Newark, Del., USA) and randomfields were counted under the light microscopy with a standardized grid.The plates were done in triplicates and the invasion index was expressedby the percent of cells that invade through occluded membrane (InvasionChamber) divided by the percent of cells that migrated trough theuncoated membrane (control insert).

The invasion index observed was 7.5 and 5.1 respectively for controlchambers compared to invasion chambers. An elevated migratory responsewas observed in control chamber, compared to the invasion chamber.Additionally, the number of invading cells from clones with vector onlywere compared to the number of invading cells from clones thatre-expressed TARSH or NESH. The results obtained were similar to thoseobtained with control vs. invasion chamber. Even though these arepreliminary results, it suggests that TARSH and NESH re-expression inthyroid carcinoma cell lines suppress cell motility and invasion. It isperhaps not too surprising that expression of some of the genesdiffering between adenoma and carcinoma might be involved in tumorinvasion, a main distinguishing feature between benign and malignanttumors.

REFERENCES

-   1. Gharib, H. 1994. Fine-needle aspiration biopsy of thyroid    nodules: advantages, limitations, and effect. Mayo Clin Proc.    69:44-49.-   2. Mazzaferri, E. L. 1993. Management of a solitary thyroid nodule.    N Engl J Med. 328:553-559.-   3. Goellener, J. R., Gharib, H., Grant, C. S., Johnson, D. A. 1987.    Fine-needle aspiration cytology of the thyroid, 1980 to 1986. Acta    Cytol. 31:587-590.-   4. Inohara, H., Honjo, Y., Yoshii, T., Akahani, S., Yoshida, J.,    Hattori, K., Okamoto, S., Sawada, T., Raz, A., and Kubo, T. 1999.    Expression of ga lectin-3 in fineneedle aspirates as a diagnostic    marker differentiating benign from malignant thyroid neoplasms.    Cancer. 85:2475-2484.-   5. Bartolazzi, A., et al. 2001. Application of an immunodiagnostic    method for improving pre-operative diagnosis of nodular thyroid    lesions. Lancet. 357:1644-1650.-   6. Xu, X. C., el-Naggar, A. K., and Lotan, R. 1995. Differential    expression of galectin-1 and galectin-3 in thyroid tumors. Potential    diagnostic implications. Am J Pathol. 147:815-822.-   7. Cvejic, D., Savin, S., Paunovic, I., Tatic, S., Havelka, M., and    Sinadinovic, J. 1998. Immunohistochemical localization of galectin-3    in malignant and benign human thyroid tissue. Anticancer Res.    18:2637-2641.-   8. Bernet, V. J., Anderson, J., Vaishnav, Y., Solomon, B., Adair, C.    F., Saji, M., Burman, K. D., Burch, H. B., and Ringel, M. D. 2002.    Determination of galectin-3 messenger ribonucleic Acid    overexpression in papillary thyroid cancer by quantitative reverse    transcription-polymerase chain reaction. J Clin Endocrinol Metab.    87:4792-4796.-   9. Kroll, T. G., Sarraf, P., Pecciarini, L., Chen, C. J., Mueller,    E., Spiegelman, B. M., and Fletcher, J. A. 2000. PAX8-PPARgammal    fusion oncogene in human thyroid carcinoma [corrected]. Science.    289:1357-1360.-   10. Marques, A. R., Espadinha, C., Catarino, A. L., Moniz, S.,    Pereira, T., Sobrinho, L. G., and Leite, V. 2002. Expression of    PAX8-PPAR gamma I rearrangements in both follicular thyroid    carcinomas and adenomas. J Clin Endocrinol Metab. 87:3947-3952.-   11. Nikiforova, M. N., Biddinger, P. W., Caudill, C. M., Kroll, T.    G., and Nikiforov, Y. E. 2002. PAX8-PPARgamma rearrangement in    thyroid tumors: RT-PCR and immunohistochemical analyses. Am J Surg    Pathol. 26:1016-1023.-   12. Cheung, L., Messina, M., Gill, A., Clarkson, A., Learoyd, D.,    Delbridge, L., Wentworth, J., Philips, J., Clifton-Bligh, R., and    Robinson, B. G. 2003. Detection of the PAX8-PPAR gamma fusion    oncogene in both follicular thyroid carcinomas and adenomas. J Clin    Endocrinol Metab. 88:354-357.-   13. Fagin, J. A. 1995. Tumor suppressor genes in human thyroid    neoplasms: p53 mutations are associated undifferentiated thyroid    cancers. J Endocrinol Invest. 18:140-142.-   14. Haugen, B. R., Nawaz, S., Markham, N., Hashizumi, T.,    Shroyer, A. L., Werness, B., and Shroyer, K. R. 1997. Telomerase    activity in benign and malignant thyroid tumors. Thyroid. 7:337-342.-   15. Sack, M. J., Astengo-Osuna, C., Lin, B. T., Battifora, H., and    LiVolsi, V. A. 1997. HBME-1 immunostaining in thyroid fine- needle    aspirations: a useful marker in the diagnosis of carcino ma. Mod    Pathol. 10:668-674.-   16. Barden, C. B., Shister, K. W., Zhu, B., Guiter; G.,    Greenblatt, D. Y., Zeiger, M. A., and Fahey, T. J., 3rd. 2003.    Classification of follicular thyroid tumors by molecular signature:    results of gene profiling. Clin Cancer Res. 9:1792-1800.-   17. Velculescu, V. E., Zhang, L., Vogelstein, B., and    Kinzler, K. W. 1995. Serial analysis of gene expression. Science.    270:484-487.-   18. Pang, X. P., Hershman, J. M., Chung, M., and Pekary, A. E. 1989.    Characterization of tumor necrosis factor-alpha receptors in human    and rat thyroid cells and regulation of the receptors by    thyrotropin. Endocrinology. 125:1783-1788.-   19. St Croix, B., et al. 2000. Genes expressed in human tumor    endothelium. Science. 289:1197-1202.-   20. Lal, A., et al. 1999. A public database for gene expression in    human cancers. Cancer Res. 59:5403-5407.-   21. Boon, K., et al. 2002. An anatomy of normal and malignant gene    expression. Proc Natl Acad Sci USA. 99:11287-11292.-   22. Buckhaults, P., Rago, C., St Croix, B., Romans, K. E., Saha, S.,    Zhang, L., Vogelstein, B., and Kinzler, K. W. 2001. Secreted and    cell surface genes expressed in benign and malignant colorectal    tumors. Cancer Res. 61:6996-7001.-   23. Radmacher, M. D., McShane, L. M., and Simon, R. 2002. A paradigm    for class prediction using gene expression profiles. J Comput Biol.    9:505-511.-   24. Tukey, J. W. 1993. Tightening the clinical trial. Control Clin    Trials. 14:266-285.-   25. Simon, R., Radmacher, M. D., Dobbin, K., and    McShane, L. M. 2003. Pitfalls in the use of DNA microarray data for    diagnostic and prognostic classification. J Natl Cancer Inst.    95:14-18.-   26. Zhang, L., Zhou, W., Velculescu, V. E., Kern, S. E., Hruban, R.    H., Hamilton, S. R., Vogelstein, B., and Kinzler, K. W. 1997. Gene    expression profiles in normal and cancer cells. Science.    276:1268-1272.-   27. Cerutti, J., Trapasso, F., Battaglia, C., Zhang, L.,    Martelli, M. L., Visconti, R., Berlingieri, M. T., Fagin, J. A.,    Santoro, M., and Fusco, A. 1996. Block of c-myc expression by    antisense oligonucleotides inhibits proliferation of human thyroid    carcinoma cell lines. Clin Cancer Res. 2:119-126.-   28. Visconti, R., et al. 1997. Expression of the neoplastic    phenotype by human thyroid carcinoma cell lines requires NFκB p65    protein expression. Oncogene. 15:1987-1994.-   29. Pauws, E., Moreno, J. C., Tijssen, M., Baas,° F., de Vilder, J.    J., and Ris-Stalpers, C. 2000. Serial analysis of gene expression as    a tool to assess the human thyroid expression profile and to    identify novel thyroidal genes. J Clin Endocrinol Metab.    85:1923-1927.-   30. Takano, T., Hasegawa, Y., Matsuzuka, F., Miyauchi, A., Yoshida,    H., Higashiyama, T., Kuma, K., and Amino, N. 2000. Gene expression    profiles in thyroid carcinomas. Br J Cancer. 83:1495-1502.-   31. Pauws, E., van Kampen, A. H., van de Graaf, S. A., de    Vijlder, J. J., and Ris-Stalpers, C. 2001. Heterogeneity in    polyadenylation cleavage sites in mammalian mRNA sequences:    implications for SAGE analysis. Nucleic Acids Res. 29:1690-1694.-   32. Nozaki, S., Sledge Jr, G. W., and Nakshatri, H. 2001. Repression    of GADD153/CHOP by NF-κB: a possible cellular defense against    endoplasmic reticulum stress-induced cell death. Oncogene.    20:2178-2185.-   33. Jin, K., Mao, X. O., Eshoo, M. W., del Rio, G., Rao, R., Chen,    D., Simon, R. P., and Greenberg, D. A. 2002. cDN A microarray    analysis of changes in gene expression induced by neuronal hypoxia    in vitro. Neurochem Res. 27:1105-1112.-   34. Talukder, A. H., Wang, R. A., and Kumar, R. 2002. Expression and    transactivating functions of the bZIP transcription factor GADD 153    in mammary epithelial cells. Oncogene. 21:4289-4300.-   35. Nikiforova, M. N., Lynch, R. A., Biddinger, P. W., Alexander, E.    K., Dorn, G. W., 2nd, Tallini, G., Kroll, T. G., and    Nikiforov, Y. E. 2003. RAS point mutations and PAX8-PPARgamma    rearrangement in thyroid tumors: evidence for distinct molecular    pathways in thyroid follicular carcinoma. J Clin Endocrinol Metab.    88:2318-2326.-   36. Brenner, B., Koppenhoefer, U., Weinstock, C., Linderkamp, O.,    Lang, F., and Gulbins, E. 1997. Fas- or ceramide-induced apoptosis    is mediated by a Rac1-regulated activation of Jun N-terminal    kinase/p38 kinases and GADD153. J Biol Chem. 272:22173-22181.-   37. Satoh, T., Toyoda, M., Hoshino, H., Monden, T., Yamada, M.,    Shimizu, H., Miyamoto, K., and Mori, M. 2002. Activation of    peroxisbme proliferatoractivated receptor-gamma stimulates the    growth arrest and DNA-damage inducible 153 gene in non-small cell    lung carcinoma cells. Oncogene. 21:2171-2180.-   38. Gotoh, T., Araki, M., and Mori, M. 1997. Chromosomal    localization of the human arginase II gene and tissue distribution    of its mRNA. Biochem Biophys Res Commun. 233:487-491.-   39. Morris, S. M., Jr., Bhamidipati, D., and Kepka-Lenhart, D. 1997.    Human type II arginase: sequence analysis and tissue-specific    expression. Gene. 193:157-161.-   40. Russell, D. H., and McVicker, T. A. 1972. Polyamine biogenesis    in the rat mammary gland during pregnancy and lactation. Biochem J.    130:71-76.-   41. Tian, W., Boss, G. R., and Cohen, D. M. 2000. Ras signaling in    the inner medullary cell response to urea and NaCl. Am J Physiol    Cell Physiol. 278:C372-380.-   42. Hong, G., Deleersnijder, W., Kozak, C. A., Van Marck, E.,    Tylzanowski, P., and Merregaert, J. 1996. Molecular cloning of a    highly conserved mouse and human integral membrane protein (Itm1)    and genetic mapping to mouse chromosome 9. Genomics. 31:295-300.-   43. Van Hul, W., Hong, G., Wauters, J., Van Hul, E., Nowak, N.,    Shows, T. B., Willems, P. J., and Merregaert, J. 1996. Assignment of    the human integral transmembrane protein 1 gene (ITM1) to human    chromosome band 11q23.3 by in situ hybridization and YAC mapping.    Cytogenet Cell Genet. 74:218-219.-   44. Meerabux, J. M., Cotter, F. E., Kearney, L., Nizetic, D., Dhut,    S., Gibbons, B., Lister, T. A., and Young, B. D. 1994. Molecular    cloning of a novel 11q23 breakpoint associated with non-Hodgkin's    lymphoma. Oncogene. 9:893-898.-   45. Matsuo, K., Tang, S. H., and Fagin, J. A. 1991. Allelotype of    human thyroid tumors: loss of chromosome 11q13 sequences in    follicular neoplasms. Mol Endocrinol. 5:1873-1879.-   46. Ward, L. S., Brenta, G., Medvedovic, M., and Fagin, J. A. 1998.    Studies of allelic loss in thyroid tumors reveal major differences    in chromosomal instability between papillary and follicular    carcinomas. J Clin Endocrinol Metab. 83:525-530.-   47. Sood, R., et al. 2001. Cloning and characterization of 13 novel    transcripts and the human RGS8 gene from the 1q25 region    encompassing the hereditary prostate cancer (HPC1) locus. Genomics.    73:211-222.-   48. Matsuda, S., Iriyama, C., Yokozali, S., Ichigotani, Y.,    Shirafuji, N., Yamaki, K., Hayakawa, T., and Hamaguchi, M. 2001.    Cloning and sequencing of a novel human gene that encodes a putative    target protein of Nesh-SH3. J Hum Genet. 46:483-486.-   49. Ichigotani, Y., Yokozaki, S., Fukuda, Y., Hamaguchi, M., and    Matsuda, S. 2002. Forced expression of NESH suppresses motility and    metastatic dissemination of malignant cells. Cancer Res.    62:2215-2219.-   50. Zedenius, J., Wallin, G., Svensson, A., Grimelius, L., Hoog, A.,    Lundell, G., Backdahl, M., and Larsson, C. 1995. Allelotyping of    follicular thyroid tumors. Hum Genet. 96:27-32.-   51. Roque, L., Rodrigues, R., Pinto, A., Moura-Nunes, V., and    Soares, J. 2003. Chromosome imbalances in thyroid follicular    neoplasms: a comparison between follicular adenomas and carcinomas.    Genes Chromosomes Cancer. 36:292-302.-   52. Grebe, S. K., McIver, B., Hay, I. D., Wu, P. S., Maciel, L. M.,    Drabkin, H. A., Goellner, J. R., Grant, C. S., Jenkins, R. B., and    Eberhardt, N. L. 1997. Frequent loss of heterozygosity on    chromosomes 3p and 17p without VHL or p53 mutations suggests    involvement of unidentified tumor suppressor genes in follicular    thyroid carcinoma. J Clin Endocrinol Metab. 82:3684-3691.-   53. Di Renzo, M. F., et aL 1995. Overexpression of the c-MET/HGF    receptor in human thyroid carcinomas derived from the follicular    epithelium. J Endocrinol Invest. 18:134-139.-   54. Ippolito, A., Vella, V., La Rosa, G. L., Pellegriti, G.,    Vigneri, R., and Belfiore, A. 2001. Immunostaining for Met/HGF    receptor may be useful to identify malignancies in thyroid lesions    classified suspicious at fine-needle aspiration biopsy. Thyroid.    11:783-787.-   55. Hanson, E. S., and Leibold, E. A. 1998. Regulation of iron    regulatory protein 1 during hypoxia and hypoxia/reoxygenation. J    Biol Chem. 273:7588-7593.-   56. Lal, A., Peters, H., St Croix, B., Haroon, Z. A., Dewhirst, M.    W., Strausberg, R. L., Kaanders, J. H., van der Kogel, A. J., and    Riggins, G. J. 2001. Transcriptional response to hypoxia in human    tumors. J Natl Cancer Inst. 93:1337-1343.-   57. Chia, S. K., Wykoff, C. C., Watson, P. H., Han, C., Leek, R. D.,    Pastorek, J., Gatter, K C., Ratcliffe, P., and Harris, A. L. 2001.    Prognostic significance of a novel hypoxia-regulated marker,    carbonic anhydrase IX, in invasive breast carcinoma. J Clin Oncol.    19:3660-3668.-   58. Fonseca, E., Soares, P., Rossi, S., and    Sobrinho-Simoes, M. 1997. Prognostic factors in thyroid carcinomas.    Verh Dtsch Ges Pathol. 81:82-96.

1. A method for distinguishing follicular thyroid adenoma (FTA) fromfollicular thyroid carcinoma (FTC) comprising the steps of: comparingamount of an expression product of at least one gene selected from thegroup consisting of DDIT3, ARG2, ITM1, Clorf24, TARSH, and ACO1 in atest follicular thyroid specimen to the amount in a normal controlthyroid specimen, wherein the expression product is selected from thegroup consisting of protein and RNA; identifying the test follicularthyroid specimen as FTA if the amount of expression product of TARSH isequal to or greater in the test follicular thyroid specimen than in thenormal control thyroid specimen, or identifying the test follicularthyroid specimen as FTC if the amount of expression product of DDIT3,ARG2, ITM1, Clorf24, or ACO1 is greater in the test follicular thyroidspecimen than in the normal control thyroid specimen.
 2. The method ofclaim 1 wherein the at least one gene comprises DDIT3.
 3. The method ofclaim 1 wherein the at least one gene comprises ARG2.
 4. The method ofclaim 1 wherein the at least one gene comprises ITM1.
 5. The method ofclaim 1 wherein the at least one gene comprises Clorf24.
 6. The methodof claim 1 wherein the at least one gene comprises TARSH.
 7. The methodof claim 1 wherein the at least one gene comprises ACO1.
 8. The methodof claim 1 wherein the test follicular thyroid specimen is a fine-needleaspiration biopsy.
 9. The method of claim 1 wherein the test follicularthyroid specimen is a pre-operative specimen.
 10. The method of claim 1further comprising the step of determining the amount of an expressionproduct prior to the step of comparing.
 11. The method of claim 1wherein the amount of RNA is compared.
 12. The method of claim 11wherein the amount of RNA is determined by reversetranscriptase-polymerase chain reaction (RT-PCR).
 13. The method ofclaim 1 wherein the amount of protein is compared.
 14. The method ofclaim 13 wherein the amount of protein is determined using an antibody.15. The method of claim 14 wherein the antibody is contacted with ahistological preparation of the test follicular thyroid specimen.
 16. Amethod for distinguishing follicular thyroid adenoma (FTA) fromfollicular thyroid carcinoma (FTC) comprising the steps of: comparingamount of an expression product of DDIT3, ARG2, and ITM1 in a testfollicular thyroid specimen to the amount in a normal control thyroidspecimen wherein the expression product is selected from the groupconsisting of protein and RNA; identifying the test follicular thyroidspecimen as FTC if the amount of expression product of DDIT3, ARG2, orITM1 is increased in the test follicular thyroid specimen relative tothe normal control thyroid specimen.
 17. The method of claim 16 whereinthe test follicular thyroid specimen is a fine-needle aspiration biopsy.18. The method of claim 16 wherein the test follicular thyroid specimenis a pre-operative specimen.
 19. The method of claim 16 furthercomprising the step of determining the amount of an expression productprior to the step of comparing.
 20. The method of claim 16 wherein theamount of RNA is compared.
 21. The method of claim 20 wherein the amountof RNA is determined by reverse transcriptase-polymerase chain reaction(RT-PCR).
 22. The method of claim 16 wherein the amount of protein iscompared.
 23. The method of claim 22 wherein the amount of protein isdetermined using an antibody.
 24. The method of claim 23 wherein theantibody is contacted with a histological preparation of the testfollicular thyroid specimen.
 25. The method of claim 16 wherein thefollicular thyroid specimen is identified as FTC if DDIT3 and ARG2 areincreased.
 26. The method of claim 16 wherein the follicular thyroidspecimen is identified as FTC if DDIT3 and ITM1 are increased.
 27. Themethod of claim 16 wherein the follicular thyroid specimen is identifiedas FTC if ITM1 and ARG2 are increased.
 28. The method of claim 16wherein the follicular thyroid specimen is identified as FTC if DDIT3,ARG2, and ITM1 are increased.
 29. The method of claim 1 wherein thefollicular thyroid specimen is identified as FTC if at least two of saidexpression products increased.
 30. The method of claim 1 wherein thefollicular thyroid specimen is identified as FTC if at least three ofsaid expression products increased.
 31. The method of claim 1 whereinthe follicular thyroid specimen is identified as FTC if at least four ofsaid expression products increased.
 32. The method of claim 1 whereinthe follicular thyroid specimen is identified as FTC if at least five ofsaid expression products increased.